The problem of synthetically generating IP traffic matrices: initial recommendations

There exist a wide variety of network design problems that require a traffic matrix as input in order to carry out performance evaluation. The research community has not had at its disposal any information about how to construct realistic traffic matrices. We introduce here the two basic problems that need to be addressed to construct such matrices. The first is that of synthetically generating traffic volume levels that obey spatial and temporal patterns as observed in realistic traffic matrices. The second is that of assigning a set of numbers (representing traffic levels) to particular node pairs in a given topology. This paper provides an in-depth discussion of the many issues that arise when addressing these problems. Our approach to the first problem is to extract statistical characteristics for such traffic from real data collected inside two large IP backbones. We dispel the myth that uniform distributions can be used to randomly generate numbers for populating a traffic matrix. Instead, we show that the lognormal distribution is better for this purpose as it describes well the mean rates of origin-destination flows. We provide estimates for the mean and variance properties of the traffic matrix flows from our datasets. We explain the second problem and discuss the notion of a traffic matrix being well-matched to a topology. We provide two initial solutions to this problem, one using an ILP formulation that incorporates simple and well formed constraints. Our second solution is a heuristic one that incorporates more challenging constraints coming from carrier practices used to design and evolve topologies.

[1]  J. Rice Mathematical Statistics and Data Analysis , 1988 .

[2]  John A. Rice,et al.  Mathematical statistics and data analysis , by John A. Rice. Pp 595.1988. ISBN 0-534-08247-5 (Wadsworth & Brooks/Cole) , 1988 .

[3]  Anja Feldmann,et al.  Deriving traffic demands for operational IP networks: methodology and experience , 2000, SIGCOMM.

[4]  Bing Yu,et al.  Time-Varying Network Tomography: Router Link Data , 2000 .

[5]  Ibrahim Matta,et al.  BRITE: Boston University Representative Internet Topology gEnerator: A Flexible Generator of Internet Topologies , 2000 .

[6]  B. Yu,et al.  Time-varying network tomography: router link data , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).

[7]  Christophe Diot,et al.  Geographical and temporal characteristics of inter-POP flows: View from a single pop , 2002, Eur. Trans. Telecommun..

[8]  Ratul Mahajan,et al.  Measuring ISP topologies with rocketfuel , 2002, SIGCOMM 2002.

[9]  Christophe Diot,et al.  Traffic matrix estimation: existing techniques and new directions , 2002, SIGCOMM 2002.

[10]  Mikkel Thorup,et al.  Optimizing OSPF/IS-IS weights in a changing world , 2002, IEEE J. Sel. Areas Commun..

[11]  Albert G. Greenberg,et al.  Fast accurate computation of large-scale IP traffic matrices from link loads , 2003, SIGMETRICS '03.

[12]  Bin Yu,et al.  Maximum pseudo likelihood estimation in network tomography , 2003, IEEE Trans. Signal Process..

[13]  Edith Cohen,et al.  Making intra-domain routing robust to changing and uncertain traffic demands: understanding fundamental tradeoffs , 2003, SIGCOMM '03.

[14]  Mikkel Thorup,et al.  Traffic engineering with estimated traffic matrices , 2003, IMC '03.

[15]  Bin Yu,et al.  Pseudo likelihood estimation in network tomography , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[16]  Bianca Schroeder,et al.  IGP link weight assignment for transient link failures , 2003 .

[17]  Carsten Lund,et al.  An information-theoretic approach to traffic matrix estimation , 2003, SIGCOMM '03.

[18]  Emilio Leonardi,et al.  How to identify and estimate the largest traffic matrix elements in a dynamic environment , 2004, SIGMETRICS '04/Performance '04.

[19]  Konstantina Papagiannaki,et al.  A distributed approach to measure IP traffic matrices , 2004, IMC '04.

[20]  Christophe Diot,et al.  Design of IGP link weight changes for estimation of traffic matrices , 2004, IEEE INFOCOM 2004.

[21]  Mikael Johansson,et al.  Traffic matrix estimation on a large IP backbone: a comparison on real data , 2004, IMC '04.

[22]  Konstantina Papagiannaki,et al.  Structural analysis of network traffic flows , 2004, SIGMETRICS '04/Performance '04.

[23]  Chadi Barakat,et al.  Controlled use of excess backbone bandwidth for providing new services in IP-over-WDM networks , 2004, IEEE Journal on Selected Areas in Communications.

[24]  Traffic matrices: balancing measurements, inference and modeling , 2005, SIGMETRICS.

[25]  Konstantina Papagiannaki,et al.  Traffic matrices: balancing measurements, inference and modeling , 2005, SIGMETRICS '05.